Machine Learning / Predictive Analytics

Success Stories

Each year, more than 12,700 pediatric patients are diagnosed with diabetic ketoacidosis (DKA), a life threatening complication of diabetes. Texas Children’s Hospital sought a way to accurately predict risk of DKA in time for care team members to intervene before these patients suffered a severe episode.
The health system ultimately formed a multidisciplinary high risk diabetes team to devise pre- and post-discharge strategies, and DKA risk prediction tools aided by the Health Catalyst Analytics Platform built using the Late-BindingTM Data Warehouse.
Results:

30.9 percent relative reduction in recurrent DKA admissions per fiscal year.
90 percent of all patients with new onset type 1 diabetes at the Medical Center Campus have a documented RIPGC in their medical chart.
100 percent of patients with type 1 diabetes have a risk index for DKA documented every 6 months.

With nearly 20 percent of elderly patients released from a hospital being readmitted within 30 days, Allina Health is focused on providing patients optimum care and support post discharge to minimize readmissions. Focusing on 30-day potentially preventable readmissions (PPRs) as its global outcome measurement, Allina Health used key clinical variables to derive the clinical relationships between hospitalizations that determine PPRs. It further built analytic capabilities to identify opportunities for improvement in care management and to test quality improvement ideas.
Allina Health’s multipronged solution included redesigning care management processes, implementing predictive analytics to identify at-risk patients, using analytics to measure the impact of its interventions, and educating patients, families, and clinicians.
These efforts are driving measurable improvements including: 10.3 percent overall reduction in PPRs, 27 percent reduction in PPRs for patients with clinic follow-up within 5 days, and $3.7 million reduction in variable costs due to avoided readmissions.

Sepsis affects more than 750,000 hospitalized patients and results in 570,000 ED visits per year. Learn how this large medical center is tackling their sepsis care challenges by leveraging their EDW and healthcare analytics. They defined and built a sepsis registry and analytics platform in 10 weeks to measure 6 interventions and 4 outcome measures — including mortality rates, length of stay, total hospital stay and 30-day readmits.